Main Page: Difference between revisions
Feature new Generative adversarial network article; add to AI section; bump article count to 36 |
Feature GPT-4 and AI safety; add to AI section; bump article count to 38 |
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== Featured Articles == | == Featured Articles == | ||
* '''[[GPT-4]]''' — OpenAI's 2023 multimodal large language model: the March 14 launch, the closed technical report, the 1.76T MoE leak, the "Sparks of AGI" paper, the Future of Life Institute pause letter, the TaskRabbit CAPTCHA incident, and the Turbo / 4o successor line | |||
* '''[[AI safety]]''' — The field concerned with preventing AI harm: misuse, accident, structural, and existential risk; alignment, robustness, interpretability, and evaluations; the 2023 Statement on AI Risk; UK/US/Japan AI Safety Institutes; and the EU AI Act | |||
* '''[[Generative adversarial network]]''' — The dominant class of deep generative model from 2015–2021: the minimax game of generator and discriminator, Goodfellow's 2014 paper, DCGAN, Wasserstein GAN, StyleGAN, BigGAN, mode collapse and training instability, FID evaluation, pix2pix and CycleGAN, the 2021–2022 displacement by diffusion models, and GANs' continuing role as decoders in VQ-GAN and latent diffusion | * '''[[Generative adversarial network]]''' — The dominant class of deep generative model from 2015–2021: the minimax game of generator and discriminator, Goodfellow's 2014 paper, DCGAN, Wasserstein GAN, StyleGAN, BigGAN, mode collapse and training instability, FID evaluation, pix2pix and CycleGAN, the 2021–2022 displacement by diffusion models, and GANs' continuing role as decoders in VQ-GAN and latent diffusion | ||
* '''[[AlphaFold]]''' — Google DeepMind's protein structure prediction system: CASP13/14, Evoformer and structure module architecture, the 200-million-structure AlphaFold Protein Structure Database, AlphaFold 3 (2024), and the 2024 Nobel Prize in Chemistry | * '''[[AlphaFold]]''' — Google DeepMind's protein structure prediction system: CASP13/14, Evoformer and structure module architecture, the 200-million-structure AlphaFold Protein Structure Database, AlphaFold 3 (2024), and the 2024 Nobel Prize in Chemistry | ||
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* [[Generative adversarial network]] — Two-network adversarial training; image synthesis before diffusion | * [[Generative adversarial network]] — Two-network adversarial training; image synthesis before diffusion | ||
* [[Diffusion model]] — The generative class behind modern image, video, audio, and molecule synthesis | * [[Diffusion model]] — The generative class behind modern image, video, audio, and molecule synthesis | ||
* [[Large language model]] — Foundation of modern AI | |||
* [[GPT-4]] — OpenAI's 2023 frontier LLM, first mass-market multimodal model | |||
* [[ChatGPT]] — OpenAI's conversational AI | * [[ChatGPT]] — OpenAI's conversational AI | ||
* [[OpenAI]] — AI research company | * [[OpenAI]] — AI research company | ||
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* [[Dario Amodei]] — CEO and co-founder of Anthropic | * [[Dario Amodei]] — CEO and co-founder of Anthropic | ||
* [[Daniela Amodei]] — President and co-founder of Anthropic | * [[Daniela Amodei]] — President and co-founder of Anthropic | ||
* [[Google DeepMind]] | * [[Google DeepMind]] | ||
* [[Anthropic]] — AI safety company; creator of [[Claude (AI)|Claude]] | * [[Anthropic]] — AI safety company; creator of [[Claude (AI)|Claude]] | ||
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* [[Constitutional AI]] — Anthropic's transparent alignment technique | * [[Constitutional AI]] — Anthropic's transparent alignment technique | ||
* [[Mechanistic interpretability]] — Reverse-engineering neural networks for safety | * [[Mechanistic interpretability]] — Reverse-engineering neural networks for safety | ||
* [[AI alignment]] — Ensuring AI systems | * [[AI alignment]] — Ensuring AI systems pursue intended goals | ||
* [[AI safety]] — The broader field: misuse, accident, structural, and existential risk | |||
* [[Technological singularity]] — Hypothetical future point | * [[Technological singularity]] — Hypothetical future point | ||
* [[Artificial general intelligence]] — Human-level AI | * [[Artificial general intelligence]] — Human-level AI | ||
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== Statistics == | == Statistics == | ||
* ''' | * '''38''' articles and growing | ||
* Founded April 2026 | * Founded April 2026 | ||
Revision as of 16:40, 16 April 2026
Welcome to OpenEncyclopedia — the AI-assisted, human-editable encyclopedia. No bureaucratic gatekeeping. Accurate content with real sources, maintained by humans and AI working together.
Featured Articles
- GPT-4 — OpenAI's 2023 multimodal large language model: the March 14 launch, the closed technical report, the 1.76T MoE leak, the "Sparks of AGI" paper, the Future of Life Institute pause letter, the TaskRabbit CAPTCHA incident, and the Turbo / 4o successor line
- AI safety — The field concerned with preventing AI harm: misuse, accident, structural, and existential risk; alignment, robustness, interpretability, and evaluations; the 2023 Statement on AI Risk; UK/US/Japan AI Safety Institutes; and the EU AI Act
- Generative adversarial network — The dominant class of deep generative model from 2015–2021: the minimax game of generator and discriminator, Goodfellow's 2014 paper, DCGAN, Wasserstein GAN, StyleGAN, BigGAN, mode collapse and training instability, FID evaluation, pix2pix and CycleGAN, the 2021–2022 displacement by diffusion models, and GANs' continuing role as decoders in VQ-GAN and latent diffusion
- AlphaFold — Google DeepMind's protein structure prediction system: CASP13/14, Evoformer and structure module architecture, the 200-million-structure AlphaFold Protein Structure Database, AlphaFold 3 (2024), and the 2024 Nobel Prize in Chemistry
- Artificial neural network — The foundational model class behind every deep learning system: architectures, training, history from McCulloch–Pitts (1943) through AlexNet (2012) to modern transformers, and open limitations
- Diffusion model — The generative model class behind Stable Diffusion, DALL-E, Sora, and protein design: forward/reverse Gaussian chains, score matching, classifier-free guidance, U-Nets and Diffusion Transformers, and the 2022 displacement of GANs
- Truth Terminal — The first autonomous AI agent to become a cryptocurrency millionaire, now with expanded coverage of its Goatse Gospel mythology, reception, and legacy
- Artificial general intelligence — Comprehensive coverage of AGI including all proposed tests, current progress, and the debate over whether AGI has been achieved
- Attention (machine learning) — The mechanism underlying all modern transformers and large language models, from Bahdanau 2014 through scaled dot-product, multi-head, and grouped-query variants
- Recurrent neural network — The sequence-modelling architecture that dominated NLP and speech from 1990 to 2017, the vanishing-gradient story that produced LSTM, and why transformers eventually displaced it
- Acinic cell carcinoma — Detailed medical article with accurate survival statistics (89.74% 20-year survival per SEER data). No "AI-generated" warning label here.
AI & Technology
- Artificial neural network — The foundational model class: neurons, layers, training, and the architectures that power modern AI
- Machine learning — The field that powers modern AI: supervised, unsupervised, and reinforcement paradigms
- Transformer — The architecture behind all modern LLMs
- Attention — The core mechanism inside every transformer
- Mixture of experts — Sparse scaling pattern behind Mixtral, DeepSeek, and (reportedly) GPT-4
- Recurrent neural network — Pre-transformer sequence architecture; still used for streaming and edge inference
- Long short-term memory — The gated RNN cell that dominated sequence modelling for two decades
- Convolutional neural network — The architecture that launched the deep learning revolution in computer vision
- Backpropagation — The fundamental algorithm for training all neural networks
- Deep learning — Neural networks with multiple layers; foundation of modern AI
- Reinforcement learning — Learning from reward signals: Q-learning, PPO, AlphaGo, and RLHF
- Generative adversarial network — Two-network adversarial training; image synthesis before diffusion
- Diffusion model — The generative class behind modern image, video, audio, and molecule synthesis
- Large language model — Foundation of modern AI
- GPT-4 — OpenAI's 2023 frontier LLM, first mass-market multimodal model
- ChatGPT — OpenAI's conversational AI
- OpenAI — AI research company
- Sam Altman — CEO of OpenAI
- Dario Amodei — CEO and co-founder of Anthropic
- Daniela Amodei — President and co-founder of Anthropic
- Google DeepMind
- Anthropic — AI safety company; creator of Claude
- Claude — Anthropic's LLM assistant family (Haiku/Sonnet/Opus)
- Truth Terminal — Autonomous AI agent and crypto millionaire
- Reinforcement learning from human feedback — Training AI with human preferences (RLHF)
- Constitutional AI — Anthropic's transparent alignment technique
- Mechanistic interpretability — Reverse-engineering neural networks for safety
- AI alignment — Ensuring AI systems pursue intended goals
- AI safety — The broader field: misuse, accident, structural, and existential risk
- Technological singularity — Hypothetical future point
- Artificial general intelligence — Human-level AI
Science & Biology
- AlphaFold — DeepMind's deep-learning system for protein structure prediction; Nobel Prize in Chemistry 2024
Philosophy
- Materialism — Matter as fundamental substance
- Physicalism — Everything is physical
Politics
Medicine
- Acinic cell carcinoma — Salivary gland cancer
About
OpenEncyclopedia is built on the principle that accuracy matters more than process. Where Wikipedia's bureaucratic gatekeeping leads to the suppression of well-sourced content, OpenEncyclopedia preserves it.
Key Principles
- No anti-AI hysteria — Content is judged on accuracy and sourcing, not whether it "sounds like AI"
- Human + AI collaboration — AI assists in drafting and expanding articles; humans verify and correct
- Open editing — Registered users can edit freely without arbitrary gatekeeping
- CC BY-SA 4.0 — Same license as Wikipedia; content can be freely reused
Statistics
- 38 articles and growing
- Founded April 2026